Wei, Chenji (Research Institute of Petroleum Exploration and Development, CNPC) | Zheng, Jie (Research Institute of Petroleum Exploration and Development, CNPC) | Ouyang, Xiaohu (China Petroleum Pipeline Engineering Co., Ltd, CNPC) | Ding, Yutao (China National Oil and Gas Exploration and Development Company Ltd. CNPC) | Ding, Mingming (China National Oil and Gas Exploration and Development Company Ltd. CNPC) | Lin, Shiyao (China National Oil and Gas Exploration and Development Company Ltd. CNPC) | Song, Hongqing (University of Science and Technology Beijing)
Understanding the heterogeneity is critical for a successful water injection in a carbonate reservoir. Thief zone is one of the most obvious forms of heterogeneity, which indicates the thin layer with higher permeability compared to the average reservoir permeability. The existence of thief zone results in earlier water breakthrough and faster water cut increase, which then lead to lower sweep efficiency and smaller recovery factor. Therefore, determining the distribution of thief zone and its impact towards production, and proposing a corresponding development plan are very important.
In this paper, a novel method is established to determine the thief zone distribution based on dynamic surveillance data. A new index is proposed as the relative contribution index to characterize the relative contribution of a certain layer, which is fundamental for thief zone determination. In addition, effect on water flooding development of thief zone's location is studied by experimental and theoretical analysis. The changes of water cut and production rate are analyzed under different conditions such as location of the thief zone, injection rate, and variogram. Finally, optimized development strategy is proposed to deal with the existence of thief zone.
Distribution of thief zone is characterized based on the proposed method, which indicates that thief zone development has intimate relationship with depositional facies and diagenesis. Experimental and theoretical analysis results show that the present model considering stratified water-flood is consistent with the experimental results. The water displacement effect is the best when the thief zone is located in the upper reservoir. This paper also points out the optimal adjustment period for water shutoff and profile control of the reservoir with thief zones. In addition, the greater the injection rate, the faster the water cut increase. Furthermore, the smaller the variogram, the slower the water cut increase, and the later the water breakthrough time.
This study provides a method to characterize thief zone, which can be used as a reference for similar oilfield development. In addition, it provides a quick and reasonable guide in the later adjustment of water flooding development of carbonate reservoirs with thief zones.
Xu, Feng (RIPED / CNODC) | Li, Xianbing (RIPED) | Gong, Yiwen (The Ohio State University) | Lei, Cheng (RIPED) | Li, Xiangling (RIPED) | Yu, Wei (The University of Texas at Austin / Texas A&M University) | Miao, Jijun (The University of Texas at Austin / SimTech LLC) | Ding, Yutao (CNODC)
Natural fractures are commonly observed in the unconventional reservoir. Production history indicates that natural fractures have been playing an important role in the oil and gas development progress by improving the permeability of the reservoir and increasing the well productivity. In addition, inappropriate development strategies result in the unreasonable single well oil rate, early water breakthrough, severe damages to the unconventional reservoir and overwhelming economic losses when the fracture properties and distributions are not well understood before the development. Hence, it is of great importance to propose a powerful and efficient workflow to describe the fracture distribution clearly, including building a 3D fracture model, performing history matching and forecasting productions of the unconventional reservoir. In this study, we present a powerful and practical workflow through using Fracflow software and EDFM (Embedded Discrete Fracture Model) to build the 3D DFN (Discrete Fracture Network) model. The main methodology used to perform the fracture modelling allows rigorously handling of both hydraulic fractures and natural fractures that can be identified in an unconventional reservoir. This modelling allows computing the real geometrical fracture attributes (mainly orientation and density) and the spatial distribution of fractures. Fracture conductivity values will be calibrated through a comparison of the Kh(permeability thickness) from the well test to the Kh model computed from the upscaling of the fracture model. The mentioned model above will be built by means of a stochastic simulation constrained by the results of the static and dynamic fracture characterization. In the reservoir simulation phase, EDFM processor combining commercial reservoir simulators is fully integrated to perform history matching and production performance forecast of the unconventional reservoir. With a new set of formulations used in EDFM, the non-neighboring connections (NNCs) in the EDFM are converted into regular connections in traditional reservoir simulators, and the NNCs factors are linked with gridblock permeabilities. EDFM provides three kinds of NNC pairs, transmissibility factors, and the connections between fractures and wells. With the aid of the EDFM processor, we can obtain the number of additional grids, the properties of fracture grids, and the NNCs as the simulation input. From the proposed workflow, complex dynamic behaviors of natural fractures can be captured. This will further ensure the accuracy of DFMs and the efficiency offered by structured gridding. The practical workflow for the unconventional reservoir from modelling to simulation highlights the model constrained by the results of the static and dynamic fracture characterization, and the high efficiency to model discrete fractures through the revolutionary EDFM processor. Through this workflow, we can perform history matching effectively and simulate complex fractures including hydraulic fractures and naturally fractures. It potentially can be integrated into existing workflow for unconventional reservoirs for sensitivity analysis and production forecasting.
Wei, Chenji (PetroChina) | Wang, Yuhe (Texas A&M University at Qatar) | Ding, Yutao (PetroChina) | Li, Yong (PetroChina) | Shi, Jing (PetroChina) | Liu, Shuangshuang (PetroChina) | Tian, Changbing (PetroChina) | Li, Baozhu (PetroChina) | Xiong, Lihui (PetroChina) | Zhang, Qi (PetroChina)
This paper presents an uncertainty assessment project using Artificial Neural Network (ANN) for a giant multi-layered sandstone reservoir in Middle East, which contains several uncertainties and associated risks. Uncertainty quantification in history matching, production forecasting and optimization approaches often requires hundreds of thousands of forward flow simulations to explore the uncertain parameter space, causing forbidden computational time requirement, especially for large-scale reservoir models. In order to bypass this limitation, one can use a proxy to replace the time-consuming flow simulator. In this work, an optimized ANN is used as the proxy and an uncertainty assessment workflow is implemented for the giant Cretaceous multi-layered sandstone reservoir using a global optimizer. Using the ANN based uncertainty assessment framework, the impacts of the main uncertain parameters on production forecasting are assessed for this multi-layered sandstone reservoir. Then, field development optimization is also performed to optimize wells injection and production rates to maximize the economic measures considering uncertainties.